DOI QR코드

DOI QR Code

Development and effectiveness analysis of artificial intelligence STEAM education program

인공지능 융합 교육 프로그램 개발 및 효과성 분석

  • Received : 2020.12.09
  • Accepted : 2021.12.17
  • Published : 2021.02.26

Abstract

With the recent advancement of artificial intelligence technology, society is rapidly changing. Amid this change, the interest in education for artificial intelligence is also increasing. Korea aims to cultivate convergent talents with diverse knowledge and AI capabilities beyond using AI. In order to apply this realistically in the field, it is necessary to present an education method through STEAM. In this study, the curriculum of each country was analyzed and the contents of education related to artificial intelligence were divided into social, ethical, and technical dimensions. In addition, the program was developed and applied in connection with the achievement standards of various subjects. As a result of the application of the program, it was effective in enhancing students' positive attitudes toward artificial intelligence technology and creative problem-solving ability. In addition, it is significant that students' satisfaction, interest, and interest in STEAM as the subject of artificial intelligence have been enhanced.

최근 인공지능 기술의 발전으로 사회의 변화가 급속하게 이루어지고 있으며, 이러한 변화 속에서 인공지능에 대한 교육의 관심 또한 높아지고 있다. 우리나라는 AI를 활용하는 것을 넘어서 다양한 지식과 AI 역량을 겸비한 융합인재 양성을 목표로 하고 있다. 이를 현장에서 현실성 있게 적용하기 위해서는 교과 융합 및 융합 인재교육(STEAM)을 통한 교육 방법의 제시가 필요하다. 본 연구에서는 각국의 교육과정을 분석하고, 인공지능 관련 교육 내용을 사회, 윤리, 기술적 차원으로 구분한 후, 다양한 교과의 성취기준과 연계하여 프로그램을 개발하고 적용하였다. 프로그램의 적용한 결과 학생들의 인공지능 기술에 대한 긍정적인 태도와 창의적 문제 해결력을 신장에 효과가 있었다. 그리고 인공지능을 주제로 한 융합인재교육에 대한 학생들의 만족도와 흥미, 그리고 관심을 증진하였다는데 의의가 있다.

Keywords

References

  1. Joint ministries. (2019). Artificial Intelligence National Strateg
  2. Kim Ji-suk. (2014). A plan to realize convergence education (STEAM) in technology science. Journal of Korean Practical Arts Education, 27(3), 21-38.
  3. Kim Minwoong, & Kim Taehoon. (2016). A meta-analysis of the effect of technology-oriented convergence education (STEAM). Practical Arts Education Research, 22(4), 65-83.
  4. Lee Soyul, & Lee Youngjun. (2017). A plan for elementary school convergence talent education centered on SW education through case analysis of leading SW education schools. Convergence Education Research, 3, 23-34.
  5. Kim Soo-hwan, Kim Seong-hoon, & Kim Hyun-cheol. (2019). Analysis of overseas AI education trends and learning tools. Journal of the Korean Society for Computer Education, 23(2), 25-28.
  6. Lee Eunkyung. (2020). Analysis of artificial intelligence curriculum in domestic and foreign elementary and secondary schools. Journal of the Korean Society of Computer Education, 23(1), 37-44.
  7. Lee Youngho. (2019). Analysis of the impact of artificial intelligence education based on block programming language on learners' attitudes of artificial intelligence technology. Journal of the Society for Information Education, 23(2), 189-196.
  8. Yoon Jinyoung, Kim Yoomi, Jae Jihwan, & Kim Yeonhyung. (2019). A study of media art convergence talent education (STEAM) program using data science and artificial intelligence. Korean Society for Science and Art Convergence, 37(5), 265-276. https://doi.org/10.17548/ksaf.2019.12.30.265
  9. Jo Yong. (2017). Convergence Talent Education (STEAM) applicable to the school field. Ingenium, 24(4), 24-29.
  10. Baek Yoon-soo, Park Hyun-joo, Kim Young-min, Noh Seok-gu, Joo-yeon Lee, Jeong Jin-soo. (2012). Basic research for establishing the implementation direction of Convergence Talent Education (STEAM). Korea Science and Creativity Foundation Research Report.
  11. Cho Eunbyul, Lee Sunyoung, Shin Jongho, & Hong Yoonjung. (2015). Delphi analysis of core factors and expected effects of convergence education. Gifted Education Research, 25(1), 37-58.
  12. Lee Kyungjin , & Kim Kyungja. (2012). Exploring the meaning and practical possibilities of STEAM as an integrated curriculum approach. Elementary Education Research, 25(3), 55-81.
  13. Sin Munseung. (2018). A meta-analysis of the effects of the elementary school convergence talent education (STEAM) program. Integrated Curriculum Research, 12(2), 47-66. https://doi.org/10.35304/JCI.12.2.03
  14. Lee Seokjin, Kim Namsuk, Lee Yunjin, & Lee Seungjin. (2017). Meta-analysis on the effects of Creativity and Problem Solving Ability of Convergence Talent Education (STEAM)-focused on research methods and researchers. Korean Journal of Science Education, 37(1), 87-101.
  15. Lee Young-ho, Kim Seong-ae, Hong Ji-yeon, Park Jung-ho, & Gu Deok-hoe. (2019). Development of a measurement tool for analysis of satisfaction with software education for elementary and secondary students. Journal of the Society for Information Education, 23(6), 573-581.